Estimating maturity from size-at-age data: Are real-world fisheries datasets up to the task?

Wootton, Henry F; Morrongiello, John R.; Audzijonytė, Asta

doi:10.1007/s11160-020-09617-9

Cited by 4 publications

(7 citation statements)

References 44 publications

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“…(2016) and Wootton et al. (2020). Another alternative for alleviating the challenges is, for example, a priori assigning a fixed value to the exponents of the model as in Quince, Abrams, et al.…”

Section: Discussionmentioning

confidence: 97%

“…Although the age of maturity

τ

and thus the quantity of

R_{t}

vary amongst individuals even within the same population, they must be assumed as constant in the model because observations cannot be obtained for individuals in fisheries data. In practice, the age at

50

% maturity is a tacit choice as an assumed value for

τ

(Minte‐Vera et al., 2016; Wootton et al., 2020). If

τ

is also to be estimated with other parameters, the estimation process faces some technical difficulties caused by the non‐differentiable nature of the objective function with respect to the change point

τ

.…”

Section: Model Development and Challengesmentioning

confidence: 99%

“…In contrast, the trajectory matching (nonlinear least-squares) method is convoluted by unstable and intensive computation because it must solve all three Equations (1a)-(1c) numerically and iteratively fits the data until the parameter estimates converge. Furthermore, given that relatively large and mature individuals are often underrepresented in fisheries data, the trajectory matching method becomes more challenging in identifying an accurate age of maturation as discussed inHonsey et al (2016) andWootton et al (2020).Another alternative for alleviating the challenges is, for example, a priori assigning a fixed value to the exponents of the model as in,), Mollet et al (2010, andMollet, Poos, et al (2016). Unfortunately, however, such a conditional approach induces a significant shortcoming that limits the interpretability of the model regarding energy allocation mechanisms.…”

mentioning

confidence: 99%

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Estimating allometric energy allocation between somatic and gonadic growth

Shimadzu

Wang

2021

Methods Ecol Evol

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Quantifying growth patterns and energy allocation strategies is essential to comprehend the biological characteristics of organisms and their interactions with broader biological communities in which they reside. Mathematical models, such as mono‐ and diphasic allometric energy‐based growth models, play a pivotal role in delineating such body growth patterns. However, modelling approaches often face some major challenges that stem from both model nonlinearity and data limitation in practice. The present study investigates the nature of the challenges and develops a flexible diphasic allometric growth model. The proposed modelling framework offers an effective parameter estimation approach directly built upon statistical smoothing techniques and numerical optimisation methods. The simulation study undertaken demonstrates that the proposed approach can provide accurate parameter estimates. The illustrative example analyses the individual body and gonadic weight of subtropical cutlassfish Trichiurus japonicus from the cooler northern and warmer southern coasts of Taiwan. The results reveal the linear growth of fish in the south compared with those in the north, which distinctive growth pattern results from the lower dependency to body mass in the somatic and gonadic growth. The proposed unified modelling framework offers new advances in growth modelling to shed light upon the intraspecific life‐history strategies, quantifying growth patterns and energy allocation strategies.

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Section: Discussionmentioning

confidence: 97%

“…Although the age of maturity

τ

and thus the quantity of

R_{t}

50

% maturity is a tacit choice as an assumed value for

τ

(Minte‐Vera et al., 2016; Wootton et al., 2020). If

τ

τ

.…”

Section: Model Development and Challengesmentioning

confidence: 99%

mentioning

confidence: 99%

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Estimating allometric energy allocation between somatic and gonadic growth

Shimadzu

Wang

2021

Methods Ecol Evol

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“…Furthermore, female L 50 is highly variable in this species, with values ranging from 17 cm in Pernambuco, Brazil, to 30 cm in the Gulf of Paria, Trinidad (Manickchand‐Dass, 1987; Viana et al ., 2015). At a larger geographical scale, the discrepancy in reported female L 50 values [reviewed by Claro and Lindeman (2008)] may be related to the different methods employed in the parameter's calculations, use of different gonad maturation scales and/or the fish size sampled (Wootton et al ., 2020). As we have experienced in the present work, failure to include the whole size spectrum results in highly uncertain estimates.…”

Section: Discussionmentioning

confidence: 99%

“…The available data suggest divergent longevity, growth and reproduction patterns, but no formal biogeographic analysis has yet been conducted. Understanding fish life history and the drivers of variation is key to sustainable fisheries management (Audzijonyte et al ., 2016; Wang et al ., 2020; Wootton et al ., 2020).…”

Section: Introductionmentioning

confidence: 99%

Geographic variation in the life history of lane snapper Lutjanus synagris, with new insights from the warm edge of its distribution

Andrade

Vihtakari

Santos

2023

Journal of Fish Biology

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Research on life‐history variations in widely distributed fish species is needed to understand global warming impacts on populations and to improve fisheries management advice. The lane snapper Lutjanus synagris (Linnaeus, 1758) is commercially important to fisheries in the Western Central Atlantic, where spread information on its life‐history traits is available. We studied growth, age, reproduction and mortality of lane snapper in the Guatemalan Caribbean, the warmest part of its distribution range, and collated the new information with published data in a latitudinal analysis extending between 18°S and 30°N. Longevity was estimated at 11 years, and von Bertalanffy growth parameters were asymptotic length (Linf) 45.6 and 42.2 cm for females and males, respectively, the growth coefficient (K) was 0.1 year−1 and the theoretical age at zero length (t0) was −4.4 years. Lane snapper grew slowest in April, prior to the rainy season, and at the onset of the reproductive season, which lasted from May to October. Fifty percent of female and male lane snappers matured at 23 and 17 cm, corresponding to 3.5 and 2.4 years of age respectively. A regional multivariate analysis found seawater temperature to be an important driver of life‐history variation. Lane snapper lifespan was shorter at the warm edge of its distribution range, and maximum size and peak reproductive investment were negatively related to sea surface temperature. The trade‐offs in lane snapper life‐history traits and phenology likely enhance its fitness to differing environments. Interpolation from the present regional estimates to less‐studied regions of the Caribbean is useful for preliminary understanding of reaction norms and harvest potentials.

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A novel statistical approach to deal with spatial bias in maturity ogive estimation

Cousido-Rocha,

Izquierdo,

Martínez-Minaya

et al. 2024

Can. J. Fish. Aquat. Sci.

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The proportion of mature fish at length is one of the most important population attributes when evaluating reproductive potential for fish stock assessment purposes. Bias in maturity ogive parameters can lead to fishery management decisions based on misspecified biological reference points. These parameters can vary spatially and temporally, and this variability should be understood and included in the assessment models. However, integrating this variability becomes challenging when specific spatial-dependent ogives cannot be used in the stock assessment model. Hence, this study proposes a novel use of a multivariate response Bayesian regression model, employing an integrated nested Laplace approximation to estimate a single global maturity ogive using data from various spatial areas. This model explicitly accounts for differences in the sampling process and combines in formation from different areas to estimate shared maturity ogive parameters using joint-likelihood procedures. The model is applied to the European hake stock in ICES (International Council for the Exploration of the Sea) Divisions 27.8.c and 27.9.a, serving as a practical guide. In this model, we have considered different predictors to handle the relationship between the probability of being mature and the length and year covariates. Our results suggest that the logistic formulation correctly captures the relationship between the probability of being mature and length. For year variability, including a year factor covariate or year random effect in the predictor model produces similar values of goodness of fit measures

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Estimating maturity from size-at-age data: Are real-world fisheries datasets up to the task?

Cited by 4 publications

References 44 publications

Estimating allometric energy allocation between somatic and gonadic growth

Estimating allometric energy allocation between somatic and gonadic growth

Geographic variation in the life history of lane snapper Lutjanus synagris, with new insights from the warm edge of its distribution

A novel statistical approach to deal with spatial bias in maturity ogive estimation

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